Hyperpolarized Magnetic Resonance Research Articles

Machine learning and magnetic resonance image texture analysis predicts accelerated lung function decline in ex-smokers with and without chronic obstructive pulmonary disease.

Our objective was to train machine-learning algorithms on hyperpolarized magnetic resonance imaging (MRI) datasets to generate models of accelerated lung function decline in participants with and without chronic-obstructive-pulmonary-disease. We hypothesized that hyperpolarized gas MRI ventilation, machine-learning, and multivariate modeling could be combined to predict clinically-relevant changes in forced expiratory volume in 1s ( ) across 3 years. Hyperpolarized MRI was acquired using a coronal Cartesian fast gradient recalled echo sequence with a partial echo and segmented using a k-means clustering algorithm. A maximum entropy mask was used to generate a region-of-interest for texture feature extraction using a custom-developed algorithm and the PyRadiomics platform. The principal component and Boruta analyses were used for feature selection. Ensemble-based and single machine-learning classifiers were evaluated using area-under-the-receiver-operator-curve and sensitivity-specificity analysis. We evaluated 88 ex-smoker participants with months follow-up data, 57 of whom (22 females/35 males, years) had negligible changes in and 31 participants (7 females/24 males, years) with worsening . In addition, 3/88 ex-smokers reported a change in smoking status. We generated machine-learning models to predict decline using demographics, spirometry, and texture features, with the later yielding the highest classification accuracy of 81%. The combined model (trained on all available measurements) achieved the overall best classification accuracy of 82%; however, it was not significantly different from the model trained on MRI texture features alone. For the first time, we have employed hyperpolarized MRI ventilation texture features and machine-learning to identify ex-smokers with accelerated decline in with 82% accuracy.

436 Immunotherapy Sensitization via Tumor Acidosis Mitigation by Esomeprazole Monitored with MRI

OBJECTIVES/GOALS: Acidity and the lactate-to-pyruvate ratio correlate with immunotherapy resistance. AcidoCEST MRI and hyperpolarized magnetic resonance spectroscopy (HP-MRS) measure extracellular pH and lactate-to-pyruvate ratio. We will establish a baseline for these biomarkers then observe changes after combination esomeprazole and immunotherapy. METHODS/STUDY POPULATION: We used multiple melanoma models created via serial in vivo passage under immunotherapeutic pressure (FVAX, CTLA-4, PD-1, PD-L1). We used four of these corresponding to 25%, 50%, 75% and 100% resistance (TMT, F2, F3, and F4, respectively). HP-MRS was performed two weeks post implantation in male BL6 mice with AcidoCEST MRI 2-3 days later. Tumors were implanted in additional mice and grown for 1 week. We used esomeprazole as a possible immunotherapy sensitizer. Esomeprazole (or PBS) alone and in combination with immune checkpoint blockade (ICB; αCTLA-4, αPD-1) was then conducted every 3 days for 3 doses. ICB was administered 3h after esomeprazole. AcidoCEST MRI was performed the day after the final dose of combination therapy and 3h after esomeprazole (or PBS) alone. HP-MRS was performed 2-3 days after acidoCEST MRI. RESULTS/ANTICIPATED RESULTS: There was a statistical increase in the lactate-to-pyruvate ratio of the F4 group compared with TMT, F2, and F3 groups (p < 0.05). The TMT, F2, and F3 groups did not differ significantly. The extracellular pH (pHe) of the TMT group was statistically lower than the F2 and F4 groups (p < 0.05). The pHe did not differ significantly between the TMT and F3 groups nor the F2, F3, and F4 groups. The lactate-to-pyruvate ratio and pHe after combination treatment with esomeprazole and ICB did not differ compared to PBS+ICB control. Treatment with esomeprazole alone generated higher lactate-to-pyruvate ratio compared with PBS alone. Tumor volume curves and survival curves of mice bearing F4 tumors treated with esomeprazole combination with ICB showed no difference compared with PBS+ICB, PBS alone, and esomeprazole alone. DISCUSSION/SIGNIFICANCE: We differentiated between the 100% and 25% resistant models with both pHe and lactate-to-pyruvate ratio, although the pHe was counterintuitive. Esomeprazole was ineffective, but other potential sensitizers exist. A non-invasive clinical imaging tool and sensitizer would permit more personalized treatment plans so treatment is more effective.

Abstract 6165: Early detection of pancreatic cancer by hyperpolarized magnetic resonance

Abstract Introduction: Pancreatic cancer is difficult to diagnose due to its asymptomatic presentation at early stages. Therefore, there is an unmet need for non-invasive imaging markers that can help identify the aggressive pancreatic lesions at an early time point. One of the most promising imaging biomarkers is the conversion of hyperpolarized (HP) pyruvate to lactate1-3. With HP metabolic imaging, the conversion will be monitored among different premalignant models at different timepoints as well as tested against pancreatitis, a known confounder of pancreatic cancer in the clinic. Methods: HP [1-13C]pyruvate Magnetic Resonance Spectroscopy (MRS) was employed to study the metabolic processes in tamoxifen inducible genetically engineered mouse models (P48CreERT2;LSL-KrasG12D(iKC)) with pre-invasive pancreatic intraepithelial neoplasia (PanIN) precursor lesions, invasive pancreatic cancer model (P48CreERT2;LSL-KrasG12D; LSL-p53R172H (iKPC)) and control animals (P48CreERT2 (iC)) at 7T Bruker MRI scanner. These mice were imaged before tamoxifen induction at 10-, 20-, and 30-weeks post induction. For the pancreatitis model, iC and iKC mice they were treated with caerulein for three weeks, 7 weeks after tamoxifen induction. The pancreatitis mice were imaged 24 hours after the last caerulein injection. Results/Discussion: HP lactate-to-pyruvate ratio is increased in the cancer models compared to the control model. In the iKPC mouse model, at the 20-week post induction imaging there was a significant increase of the lactate-to-pyruvate ratio compared to the 10-weektime point after induction. The 20-week iKPC time point ratio compared to the iKC and control mouse models was significantly higher, indicating the aggressive nature of the disease. Even in the iKC model there is a slight increase of the lactate-to-pyruvate ratio at 20-weeks post induction compared to both previous time points, pre-induction and 10-week. No change in the lactate-to-pyruvate ratio was not observed with the pancreatitis phenotype. In the future, we plan on imaging at earlier timepoints or at smaller intervals in the iKPC model, to observe the exact moment the metabolism switches to lactate. Conclusion: Our data demonstrates that the metabolic flux to lactate is only increasing in the premalignant models of pancreatic cancer but not in the pancreatitis model, suggesting that the differentiation between early pancreatic cancer and pancreatitis can be achieved by hyperpolarized metabolic imaging. We are currently in the process of translating this in a clinical trial at MD Anderson Cancer Center. Citation Format: Paytience L. Smith, José S. Enriquez, Rian Howell, Olivereen Le Roux, Shivanand Pudakalakatti, Prasanta Dutta, Florencia Mcallister, Pratip Bhattacharya. Early detection of pancreatic cancer by hyperpolarized magnetic resonance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6165.

Abstract 4157: Combining hyperpolarized magnetic resonance and positron emission tomography to interrogate prostate cancer metabolism

Abstract Background: There is an unmet clinical need for imaging biomarkers to distinguish indolent from aggressive prostate cancer (PCa). Many advanced and aggressive PCa patients receiving anti-androgens (enzalutamide) develop resistance. It is hypothesized that dysregulated cell metabolism is a key driver for PCa progression and therapy resistance. Two pathways commonly involved in PCa are glycolysis and fatty acid metabolism. Therefore, metabolic imaging and metabolomics were performed on enzalutamide sensitive/resistant, Androgen Receptor dependent (AR+) and AR independent (AR-) patient derived xenograft (PDX) tumors. To interrogate both pathways, [1-13C]-pyruvate hyperpolarized magnetic resonance spectroscopy (HP-MRS) and [18F]-fluorodeoxyglucose positron emission tomography (18F-FDG) for glycolysis, and [18F]-fluoro-pivalic acid positron emission tomography (18F-FPIA) for fatty acid metabolism were employed. 1H Nuclear Magnetic Resonance (NMR) spectroscopy and liquid chromatography with tandem mass spectrometry (LC-MS-MS) were employed for validation purposes. Methods: [1-13C]-labeled pyruvic acid was hyperpolarized using a DNP HyperSense polarizer following standard protocol. Anatomical MRI and 13C-MRS were obtained on different PCa PDX mouse models at two different time points using a Bruker 7T scanner. The PDX models included AR+ enzalutamide sensitive (183-A, 180-30), AR+ enzalutamide resistant (274-4), and AR- (144-4, 114-B). The time points imaged were before and after 7 days of treatment with enzalutamide. 1H-NMR spectroscopy was performed on extracted tissue. Simultaneously, 18F-FPIA-PET imaging were acquired on the same models on an Albira trimodal PET station. Results: The dynamic metabolic flux ratio, lactate-to-pyruvate (Lac/Pyr) was determined in vivo and used as a treatment response marker. The Lac/Pyr ratios were significantly higher in resistant tumors compared to sensitive tumors (p<0.01). The enzalutamide sensitive group had a lower Lac/Pyr ratio after treatment, while the enzalutamide resistant group had a higher Lac/Pyr ratio. After treatment, there was also a decrease in [18F]-FDG uptake, corresponding to the HP-MRS data. This was expected as both Pyruvate and [18F]-FDG interrogate the glycolytic pathway. As for the fatty acid metabolic imaging, PET imaging also revealed that [18F]-FPIA is transported into the tumors, and we are currently exploring how its uptake varies between AR (+/-) PCa-PDX tumors and enzalutamide resistant/sensitive models. Ex vivo NMR and mass spectrometry-based metabolomics validated the in vivo HP-MRS data with higher lactate levels in drug resistant tumors. Conclusion: Combining HP-MRS and PET presents an exciting opportunity to realize imaging-based personalized medicine in different AR (+/-) PCa-PDX preclinical models by interrogating glycolysis and fatty acid oxidation pathways. Citation Format: Muxin Wang, José S. Enriquez, Prasanta Dutta, Jenny Han, Peter Shepherd, Daniel Frigo, Federica Pisaneschi, Pratip K. Bhattacharya. Combining hyperpolarized magnetic resonance and positron emission tomography to interrogate prostate cancer metabolism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4157.

Abstract 4156: Monitoring early chemotherapy response in murine pancreatic ductal adenocarcinoma using non-invasive hyperpolarized magnetic resonance spectroscopic imaging with 13C-pyruvate

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is a rarely operable cancer with a very poor prognosis. Nearly 100% of affected patients receive one of two alternative first-line chemotherapies during the course of their disease: 1.) Gemcitabine-Abraxane (G/A) or 2.) FOLFIRINOX. Treatment success varies widely between the patients due to individual molecular, structural tumor and metabolic heterogeneity. In this project, we use hyperpolarized 13C-pyruvate magnetic resonance spectroscopic imaging (HP-MRSI) to non-invasively characterize early metabolic changes in murine endogenous PDAC in response to the mentioned chemotherapies. Methods: 18 KPC (Ptf1awt/cre(C)Kraswt/G12D(K)Trp53fl/fl(P)) mice with 74 distinct tumour nodules, visually identified based on T2-weighted anatomical imaging, were used in this study. The conversion of pyruvate to lactate was detected by HP-MRSI, performed on 7 T preclinical system using modified 3D balanced steady-state free precession (bSSFP) sequence on day 0 pre-therapy and on day 3 post-therapy. 100μg/g G (intraperitoneally) and 30μg/g A (intravenously) were applied twice on day 0 post-scan and day 2 (n=6). FOLFIRINOX (60μg/g 5-Fluoruracil, 27μg/g Irinotecan, 12.8μg/g Oxaliplatin, 60μg/g Leucovorin) was injected intravenously once on day 0 post-scan (n=6). Vehicle mice (n=6) were left untreated. Area under the curves (AUC) of lactate to pyruvate time-courses (AUCl/AUCp) were calculated. Primary murine PDAC cell lines were established from biopsies of 58 imaging region, sequenced using 3’RNA-Seq (Poly-ASeq) method and analysed using Dseq2 R package. Results: G/A and FOLFIRINOX-treated tumors exhibited heterogeneous metabolic responses in distinct nodules, while non-treated group tumors remained stable. A significant difference in metabolic changes (p = 0.01, ANOVA) from day 0 to day 3 was observed between FOLFIRINOX, G/A, and non-treated groups. Low glycolytic tumors showed a positive trend, more pronounced with FOLFIRINOX than G/A treatment. Metabolically active nodules with high AUCl/AUCp on day 0 reduced lactate turnover under therapy. These findings suggest that metabolic HP-MRSI can detect treatment-induced changes in tumor composition and subtype-specific epithelial/mesenchymal plasticity, correlating with the metabolic phenotype. Further investigation will include histology, subtype-specific biomarkers, transcriptional signatures, and regional transcriptome analysis to explain molecular changes in metabolism. Conclusions: We have applied a non-invasive approach for detection of metabolic changes under chemotherapy in murine PDAC. These findings will contribute in the long term to the establishment of predictive imaging biomarkers for PDAC. Citation Format: Irina Heid, Anna-Maria Schmidmüller, Simon Baller, Jason G. Skinner, Geoffrey J. Topping, Wolfgang Gottwald, Hussein Trabulssi, Rupert Öllinger, Katja Steiger, Roland Rad, Franz Schilling, Rickmer F. Braren. Monitoring early chemotherapy response in murine pancreatic ductal adenocarcinoma using non-invasive hyperpolarized magnetic resonance spectroscopic imaging with 13C-pyruvate [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4156.

O-26 - Combining Positron Emission Tomography and Hyperpolarized Magnetic Resonance to Interrogate Prostate Cancer Metabolism

O-26 - Combining Positron Emission Tomography and Hyperpolarized Magnetic Resonance to Interrogate Prostate Cancer Metabolism

A Study on the Diazo-Transfer Reaction Using o-Nitrobenzenesulfonyl Azide

Abstract 15N-Labeled azides have a great potential as practical and effective tags for vibrational probing and hyperpolarized magnetic resonance imaging of biomolecules. They can be synthesized by reaction of primary amines with a 15N-labeled diazo-transfer reagent. TfNN15N, a γ-15N-labeled diazo-transfer reagent, was developed to prepare β-15N-labeled azides; these are vibrational probes devoid of strong spectral interference by Fermi resonance. To overcome the stability and safety problems associated with TfNN15N, there is a strong demand for the development of a novel γ-15N-labeled diazo-transfer reagent. We present a study on the diazo-transfer reaction using o-nitrobenzenesulfonyl azide (o-NsN3). o-NsNN15N, a γ-15N-labeled diazo-transfer reagent, was newly developed and found to be better than TfNN15N with respect to its physicochemical properties and ease of synthesis. Unlike TfNN15N, however, o-NsNN15N was found to afford a mixture of β- and γ-15N-labeled azides rather than the β-15N-labeled azide alone. A mechanism for the diazo-transfer reaction of o-NsNN15N with primary amines is proposed to explain the formation of such isotopomeric mixtures.

Multi-sample/multi-nucleus parallel polarization and monitoring enabled by a fluid path technology compatible cryogenic probe for dissolution dynamic nuclear polarization

Low throughput is one of dissolution Dynamic Nuclear Polarization (dDNP) main shortcomings. Especially for clinical and preclinical applications, where direct 13C nuclei polarization is usually pursued, it takes hours to generate one single hyperpolarized (HP) sample. Being able to hyperpolarize more samples at once represents a clear advantage and can expand the range and complexity of the applications. In this work, we present the design and performance of a highly versatile and customizable dDNP cryogenic probe, herein adapted to a 5 T “wet” preclinical polarizer, that can accommodate up to three samples at once and, most importantly, it is capable of monitoring the solid-state spin dynamics of each sample separately, regardless of the kind of radical used and the nuclear species of interest. Within 30 min, the system was able to dispense three HP solutions with high repeatability across the channels (30.0 ± 1.2% carbon polarization for [1-13C]pyruvic acid doped with trityl radical). Moreover, we tested multi-nucleus NMR capability by polarizing and monitoring simultaneously 13C, 1H and 129Xe. Finally, we implemented [1-13C]lactate/[1-13C]pyruvate polarization and back-to-back dissolution and injection in a healthy mouse model to perform multiple-substrate HP Magnetic Resonance Spectroscopy (MRS) at 14.1 T.

Nanomaterials for hyperpolarized nuclear magnetic resonance and magnetic resonance imaging.

Nanomaterials play an important role in the development and application of hyperpolarized materials for magnetic resonance imaging (MRI). In this context they can not only act as hyperpolarized materials which are directly imaged but also play a role as carriers for hyperpolarized gases and catalysts for para-hydrogen induced polarization (PHIP) to generate hyperpolarized substrates for metabolic imaging. Those three application possibilities are discussed, focusing on carbon-based materials for the directly imaged particles. An overview over recent developments in all three fields is given, including the early developments in each field as well as important steps towards applications in MRI, such as making the initially developed methods more biocompatible and first imaging experiments with spatial resolution in either phantoms or in vivo studies. Focusing on the important features nanomaterials need to display to be applicable in the MRI context, a wide range of different approaches to that extent is covered, giving the reader a general idea of different possibilities as well as recent developments in those different fields of hyperpolarized magnetic resonance. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > In Vivo Nanodiagnostics and Imaging.

Developing a metabolic clearance rate framework as a translational analysis approach for hyperpolarized 13C magnetic resonance imaging

Hyperpolarized carbon-13 magnetic resonance imaging is a promising technique for in vivo metabolic interrogation of alterations between health and disease. This study introduces a formalism for quantifying the metabolic information in hyperpolarized imaging. This study investigated a novel perfusion formalism and metabolic clearance rate (MCR) model in pre-clinical stroke and in the healthy human brain. Simulations showed that the proposed model was robust to perturbations in T1, transmit B1, and kPL. A significant difference in ipsilateral vs contralateral pyruvate derived cerebral blood flow (CBF) was detected in rats (140 ± 2 vs 89 ± 6 mL/100 g/min, p < 0.01, respectively) and pigs (139 ± 12 vs 95 ± 5 mL/100 g/min, p = 0.04, respectively), along with an increase in fractional metabolism (26 ± 5 vs 4 ± 2%, p < 0.01, respectively) in the rodent brain. In addition, a significant increase in ipsilateral vs contralateral MCR (0.034 ± 0.007 vs 0.017 ± 0.02/s, p = 0.03, respectively) and a decrease in mean transit time (31 ± 8 vs 60 ± 2 s, p = 0.04, respectively) was observed in the porcine brain. In conclusion, MCR mapping is a simple and robust approach to the post-processing of hyperpolarized magnetic resonance imaging.

Exploiting metabolic vulnerabilities after anti-VEGF antibody therapy in ovarian cancer

Despite modest clinical improvement with anti-vascular endothelial growth factor antibody (AVA) therapy in ovarian cancer, adaptive resistance is ubiquitous and additional options are limited. A dependence on glutamine metabolism, via the enzyme glutaminase (GLS), is a known mechanism of adaptive resistance and we aimed to investigate the utility of a GLS inhibitor (GLSi). Our invitro findings demonstrated increased glutamine abundance and a significant cytotoxic effect in AVA-resistant tumors when GLSi was administered in combination with bevacizumab. Invivo, GLSi led to a reduction in tumor growth as monotherapy and when combined with AVA. Furthermore, GLSi initiated after the emergence of resistance to AVA therapy resulted in a decreased metabolic conversion of pyruvate to lactate as assessed by hyperpolarized magnetic resonance spectroscopy and demonstrated robust antitumor effects with a survival advantage. Given the increasing population of patients receiving AVA therapy, these findings justify further development of GLSi in AVA resistance.

Abstract 6222: Comprehensive monitoring of pyruvate metabolism in cancer cells and tumors reveals vulnerability to metabolic inhibition therapy with small molecules

Abstract Introduction: Pyruvate(Pyr) metabolism is a keystone in cancer metabolism, as well as normal cells, and has two major metabolic fluxes; Glycolysis and Oxidative Phosphorylation (OXPHOS). Especially in cancer cells, increased Pyr metabolism meets the demand of higher energy consumption during rapid cell growing state. Therefore, monitoring tumor Pyr metabolic flux in vitro and in vivo should be necessary to develop a therapeutic strategy using small molecules which can inhibit the fluxes.Aim: We performed in vitro metabolic analysis on pancreatic cancer cells (MiaPaCa2) and applied a novel in vivo imaging technology “hyperpolarized 13C-pyruvate magnetic resonance spectroscopic imaging (HP-MRSI)” to dynamic monitoring of the impact of Glycolysis and OXPHOS inhibitors on the MiaPaCa2 xenografts. Methods: We used a novel LDH inhibitor “NCI-006” for Glycolysis inhibition and Mitochondrial Complex 1(MC1) Inhibitor "Metformin(Met)", which is already clinically available, and “IACS-010759(IACS)” for OXPHOS inhibition, in vitro and in vivo. Extracellular flux (EXF) analysis and HP-MRSI were performed before and after administration of each or both to assess inhibitor impact on metabolic flux in vitro and in vivo, respectively. Results: HP-MRSI confirmed that LDH activity in the tumor was suppressed by NCI-006 (83.3±4.4% decrease) and accelerated by Met (69.9±6.6% increase) and IACS (88.6±25.1% increase). We confirmed these in vivo observations are fully consistent with the effect of those inhibitors in vitro on the energy profile of MiaPaCa2, and also the close correlation of these data with the results of the ex vivo LDH activity assay, suggesting HP-MRSI can reliably monitor in vivo on target effects of the inhibitors without need for tissue sampling. In addition, combined treatment with the NCI-006 and MC1 inhibitor significantly suppressed in vitro cell growth and tumor growth in an efficacy study of MiaPaCa2 xenografts, compared to each single administration. Apoptosis assay showed the combined treatment induced apoptosis in MIA Paca2 cells. Conclusion: Using EXF analyzer and HP-MRSI revealed that Glycolysis inhibition redirects tumor Pyr toward OXPHOS and also MC1 inhibition redirects tumor Pyr toward Glycolysis. Combination therapy suppresses metabolic plasticity, causing metabolic quiescence in vitro and tumor growth inhibition in vivo. HP-MRSI is thought to be useful for pancreatic cancer patients to establish the current treatment model because of no need to obtain clinical samples, such as patients-derived cancer cells or spheroid from the patients. The current proof of concept can be of great value in developing new therapeutic strategies using metabolic inhibitors to treat cancers. Citation Format: Nobu Oshima, Yuki Aisu, Shigeo Hisamori, Shigeru Tsunoda, Hiroki Hashida, Kenji Uryuhara, Hiroyuki Kobayashi, Masato Kondo, koji Kitamura, Satoshi Kaihara, Kazutaka Obama, Krishna Murali, Len Neckers. Comprehensive monitoring of pyruvate metabolism in cancer cells and tumors reveals vulnerability to metabolic inhibition therapy with small molecules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6222.

Abstract 2484: Hyperpolarized magnetic resonance spectroscopy assessment of the metabolic effects of glutaminase inhibitor therapy in an ovarian cancer model

Abstract Introduction: Ovarian cancer accounts for more deaths than any other cancer of the female reproductive system despite advances in targeted drugs such as anti-VEGF antibody (AVA). Additionally, resistance to AVA therapy is nearly ubiquitous given the occurrence of metabolic adaptations such as a dependence on glutamine metabolism via the enzyme glutaminase. Objectives: To examine the metabolic vulnerability of AVA-resistant cancer with glutaminase inhibitor (GLSi) therapy and to test the utility of hyperpolarized magnetic resonance spectroscopy (HP-MRS) for assessing changes in lactate metabolism associated with GLSi treatment following injection of hyperpolarized [1-13C] pyruvate. Methods: We used a well-characterized SKOV3ip1 orthotopic mouse model of high-grade serous ovarian cancer with adaptive resistance to AVA (bevacizumab) treatment. Following three weeks of GLSi and bevacizumab treatment, we performed HP-MRS imaging to directly and non-invasively compare metabolic changes between the treatment groups of bevacizumab monotherapy versus a combined treatment of bevacizumab plus GLSi therapy. Upon injection of hyperpolarized [1-13C] pyruvate, we quantitatively assessed a normalized lactate ratio (nLac), defined as the 13C resonance signal of lactate divided by the sum of the pyruvate and lactate signals, sixty seconds after injection. GLSi treatment effect was subsequently compared between GLSi monotherapy, bevacizumab monotherapy and control mice receiving no therapy. This was performed via gross necropsy to assess disease burden and quantification of tumor weight and nodule number. Results: Significance analysis microarrays (SAM) of bevacizumab treated tumors from the mouse models revealed greater glutamine and glutamate abundance in all tissues suggestive of a glutamine dependence in AVA resistant tumors that could be susceptible to glutaminase inhibition. The in vivo HP-MRS provided a direct and non-invasive investigation of pyruvate metabolism of tumors in situ. Our analysis indicated that the pyruvate-to-lactate conversion was significantly reduced in vivo by GLSi treatment (0.337 vs 0.178, p=0.0002), suggestive of therapeutic efficacy of GLSi in the setting of AVA-resistant tumors. Consistent with this, we observed a statistically significant reduction in tumor weight (0.05g vs 0.62g and 0.64g, p&amp;lt;0.01) and tumor nodule number (n=3.3 vs n=12.8 and n=13.9, p&amp;lt;0.05) in mice treated with a combination of bevacizumab and GLSi compared to the control group, or GLSi monotherapy, respectively. Conclusions: Using HP-MRS in vivo, we directly monitored metabolic changes occurring after GLSi treatment. These findings are consistent with the notion of glutamine dependence being an important resistance mechanism to AVA therapy and imply potential future use of HP-MRS in monitoring therapeutic efficacy in a clinical realm. Citation Format: Deanna Glassman, Mark S. Kim, Prasanta Dutta, Charles V. Kingsley, Emine Bayraktar, Yutuan Wu, Elaine Stur, Lingegowda S. Mangala, Katherine Foster, Sanghoon Lee, Timothy A. Yap, Shannon N. Westin, Pratip Bhattacharya, Anil K. Sood. Hyperpolarized magnetic resonance spectroscopy assessment of the metabolic effects of glutaminase inhibitor therapy in an ovarian cancer model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2484.

Biomedical Imaging in Experimental Models of Cardiovascular Disease.

Major advances in biomedical imaging have occurred over the last 2 decades and now allow many physiological, cellular, and molecular processes to be imaged noninvasively in small animal models of cardiovascular disease. Many of these techniques can be also used in humans, providing pathophysiological context and helping to define the clinical relevance of the model. Ultrasound remains the most widely used approach, and dedicated high-frequency systems can obtain extremely detailed images in mice. Likewise, dedicated small animal tomographic systems have been developed for magnetic resonance, positron emission tomography, fluorescence imaging, and computed tomography in mice. In this article, we review the use of ultrasound and positron emission tomography in small animal models, as well as emerging contrast mechanisms in magnetic resonance such as diffusion tensor imaging, hyperpolarized magnetic resonance, chemical exchange saturation transfer imaging, magnetic resonance elastography and strain, arterial spin labeling, and molecular imaging.

Prediction of multiple pH compartments by deep learning in magnetic resonance spectroscopy with hyperpolarized 13C-labelled zymonic acid

BackgroundHyperpolarization enhances the sensitivity of nuclear magnetic resonance experiments by between four and five orders of magnitude. Several hyperpolarized sensor molecules have been introduced that enable high sensitivity detection of metabolism and physiological parameters. However, hyperpolarized magnetic resonance spectroscopy imaging (MRSI) often suffers from poor signal-to-noise ratio and spectral analysis is complicated by peak overlap. Here, we study measurements of extracellular pH (pHe) by hyperpolarized zymonic acid, where multiple pHe compartments, such as those observed in healthy kidney or other heterogeneous tissue, result in a cluster of spectrally overlapping peaks, which is hard to resolve with conventional spectroscopy analysis routines.MethodsWe investigate whether deep learning methods can yield improved pHe prediction in hyperpolarized zymonic acid spectra of multiple pHe compartments compared to conventional line fitting. As hyperpolarized 13C-MRSI data sets are often small, a convolutional neural network (CNN) and a multilayer perceptron (MLP) were trained with either a synthetic or a mixed (synthetic and augmented) data set of acquisitions from the kidneys of healthy mice.ResultsComparing the networks’ performances compartment-wise on a synthetic test data set and eight real kidney data shows superior performance of CNN compared to MLP and equal or superior performance compared to conventional line fitting. For correct prediction of real kidney pHe values, training with a mixed data set containing only 0.5% real data shows a large improvement compared to training with synthetic data only. Using a manual segmentation approach, pH maps of kidney compartments can be improved by neural network predictions for voxels including three pH compartments.ConclusionThe results of this study indicate that CNNs offer a reliable, accurate, fast and non-interactive method for analysis of hyperpolarized 13C MRS and MRSI data, where low amounts of acquired data can be complemented to achieve suitable network training.

Ketohexokinase-mediated fructose metabolism is lost in hepatocellular carcinoma and can be leveraged for metabolic imaging.

The ability to break down fructose is dependent on ketohexokinase (KHK) that phosphorylates fructose to fructose-1-phosphate (F1P). We show that KHK expression is tightly controlled and limited to a small number of organs and is down-regulated in liver and intestinal cancer cells. Loss of fructose metabolism is also apparent in hepatocellular adenoma and carcinoma (HCC) patient samples. KHK overexpression in liver cancer cells results in decreased fructose flux through glycolysis. We then developed a strategy to detect this metabolic switch in vivo using hyperpolarized magnetic resonance spectroscopy. Uniformly deuterating [2-13C]-fructose and dissolving in D2O increased its spin-lattice relaxation time (T1) fivefold, enabling detection of F1P and its loss in models of HCC. In summary, we posit that in the liver, fructolysis to F1P is lost in the development of cancer and can be used as a biomarker of tissue function in the clinic using metabolic imaging.

Migraine-Associated Mutation in the Na,K-ATPase Leads to Disturbances in Cardiac Metabolism and Reduced Cardiac Function.

BackgroundMutations in ATP1A2 gene encoding the Na,K‐ATPase α2 isoform are associated with familial hemiplegic migraine type 2. Migraine with aura is a known risk factor for heart disease. The Na,K‐ATPase is important for cardiac function, but its role for heart disease remains unknown. We hypothesized that ATP1A2 is a susceptibility gene for heart disease and aimed to assess the underlying disease mechanism.Methods and ResultsMice heterozygous for the familial hemiplegic migraine type 2–associated G301R mutation in the Atp1a2 gene (α2 +/G301R mice) and matching wild‐type controls were compared. Reduced expression of the Na,K‐ATPase α2 isoform and increased expression of the α1 isoform were observed in hearts from α2 +/G301R mice (Western blot). Left ventricular dilation and reduced ejection fraction were shown in hearts from 8‐month‐old α2 +/G301R mice (cardiac magnetic resonance imaging), and this was associated with reduced nocturnal blood pressure (radiotelemetry). Cardiac function and blood pressure of 3‐month‐old α2 +/G301R mice were similar to wild‐type mice. Amplified Na,K‐ATPase–dependent Src kinase/Ras/Erk1/2 (p44/42 mitogen‐activated protein kinase) signaling was observed in hearts from 8‐month‐old α2 +/G301R mice, and this was associated with mitochondrial uncoupling (respirometry), increased oxidative stress (malondialdehyde measurements), and a heart failure–associated metabolic shift (hyperpolarized magnetic resonance). Mitochondrial membrane potential (5,5´,6,6´‐tetrachloro‐1,1´,3,3´‐tetraethylbenzimidazolocarbocyanine iodide dye assay) and mitochondrial ultrastructure (transmission electron microscopy) were similar between the groups. Proteomics of heart tissue further suggested amplified Src/Ras/Erk1/2 signaling and increased oxidative stress and provided the molecular basis for systolic dysfunction in 8‐month‐old α2 +/G301R mice.ConclusionsOur findings suggest that ATP1A2 mutation leads to disturbed cardiac metabolism and reduced cardiac function mediated via Na,K‐ATPase–dependent reactive oxygen species signaling through the Src/Ras/Erk1/2 pathway.

Aiding Airway Obstruction Diagnosis With Computational Fluid Dynamics and Convolutional Neural Network: A New Perspective and Numerical Case Study

AbstractIt is challenging to locate small-airway obstructions induced by chronic obstructive pulmonary disease (COPD) directly from visualization using available medical imaging techniques. Accordingly, this study proposes an innovative and noninvasive diagnostic method to detect obstruction locations using computational fluid dynamics (CFD) and convolutional neural network (CNN). Specifically, expiratory airflow velocity contours were obtained from CFD simulations in a subject-specific 3D tracheobronchial tree. One case representing normal airways and 990 cases associated with different obstruction sites were investigated using CFD. The expiratory airflow velocity contours at a selected cross section in the trachea were labeled and stored as the database for training and testing two CNN models, i.e., ResNet50 and YOLOv4. Gradient-weighted class activation mapping (Grad-CAM) and the Pearson correlation coefficient were employed and calculated to classify small-airway obstruction locations and pulmonary airflow pattern shifts and highlight the highly correlated regions in the contours for locating the obstruction sites. Results indicate that the airflow velocity pattern shifts are difficult to directly visualize based on the comparisons of CFD velocity contours. CNN results show strong relevance exists between the locations of the obstruction and the expiratory airflow velocity contours. The two CNN-based models are both capable of classifying the left lung, right lung, and both lungs obstructions well using the CFD simulated airflow contour images with total accuracy higher than 95.07%. The two automatic classification algorithms are highly transformative to clinical practice for early diagnosis of obstruction locations in the lung using the expiratory airflow velocity distributions, which could be imaged using hyperpolarized magnetic resonance imaging.

Post-Acquisition Hyperpolarized 29Silicon Magnetic Resonance Image Processing for Visualization of Colorectal Lesions Using a User-Friendly Graphical Interface.

Medical imaging devices often use automated processing that creates and displays a self-normalized image. When improperly executed, normalization can misrepresent information or result in an inaccurate analysis. In the case of diagnostic imaging, a false positive in the absence of disease, or a negative finding when disease is present, can produce a detrimental experience for the patient and diminish their health prospects and prognosis. In many clinical settings, a medical technical specialist is trained to operate an imaging device without sufficient background information or understanding of the fundamental theory and processes involved in image creation and signal processing. Here, we describe a user-friendly image processing algorithm that mitigates user bias and allows for true signal to be distinguished from background. For proof-of-principle, we used antibody-targeted molecular imaging of colorectal cancer (CRC) in a mouse model, expressing human MUC1 at tumor sites. Lesion detection was performed using targeted magnetic resonance imaging (MRI) of hyperpolarized silicon particles. Resulting images containing high background and artifacts were then subjected to individualized image post-processing and comparative analysis. Post-acquisition image processing allowed for co-registration of the targeted silicon signal with the anatomical proton magnetic resonance (MR) image. This new methodology allows users to calibrate a set of images, acquired with MRI, and reliably locate CRC tumors in the lower gastrointestinal tract of living mice. The method is expected to be generally useful for distinguishing true signal from background for other cancer types, improving the reliability of diagnostic MRI.

Radial Flow Perfusion Enables Real-Time Profiling of Cellular Metabolism at Low Oxygen Levels with Hyperpolarized 13C NMR Spectroscopy.

In this study, we describe new methods for studying cancer cell metabolism with hyperpolarized 13C magnetic resonance spectroscopy (HP 13C MRS) that will enable quantitative studies at low oxygen concentrations. Cultured hepatocellular carcinoma cells were grown on the surfaces of non-porous microcarriers inside an NMR spectrometer. They were perfused radially from a central distributer in a modified NMR tube (bioreactor). The oxygen level of the perfusate was continuously monitored and controlled externally. Hyperpolarized substrates were injected continuously into the perfusate stream with a newly designed system that prevented oxygen and temperature perturbations in the bioreactor. Computational and experimental results demonstrated that cell mass oxygen profiles with radial flow were much more uniform than with conventional axial flow. Further, the metabolism of HP [1-13C]pyruvate was markedly different between the two flow configurations, demonstrating the importance of avoiding large oxygen gradients in cell perfusion experiments.